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Pivotal - Advanced Analytics for Telecommunications

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Innovative mobile operators need to mine the vast troves of unstructured data now available to them to help develop compelling customer experiences and uncover new revenue opportunities. In this webinar, you’ll learn how HDB’s in-database analytics enable advanced use cases in network operations, customer care, and marketing for better customer experience. Join us, and get started on your advanced analytics journey today!

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Pivotal - Advanced Analytics for Telecommunications

  1. 1. background image: 960x540 pixels - send to back of slide and set to 80% transparency Advanced Analytics for Telecommunications Bob Glithero, Principal Product Marketing Manager Vineet Goel, Product Manager
  2. 2. background image: 960x540 pixels - send to back of slide and set to 80% transparency Agenda •  Pivotal – Hortonworks Partnership •  Challenges in Customer Experience •  HDB: Hadoop-Native Analytics Database for Hortonworks Data Platform •  Sample Use Cases •  For More Information
  3. 3. Pivotal HDB + Hortonworks Hadoop Partnering for Faster Value from Data ●  Leaders in open-source Hadoop ●  Managing, analyzing, and operationalizing data at scale ●  Joint support for ODPi promotes interoperability in Hadoop + Pivotal and Hortonworks’ strategic partnership marries Pivotal’s best-in-class SQL on Hadoop, analytical database, with Hortonworks’ best-in class expertise and support for Hadoop.
  4. 4. You’re the third person I’ve been handed off to! Can’t anyone help me? 4
  5. 5. I’m not seeing any alarms...why are our customers having poor service? 5
  6. 6. Managing Experience is Complicated Then •  Basic handsets, embedded applications •  Simpler services - voice, SMS, WAP •  Experience influenced mostly inside the network Now •  From phones to hand-held computers •  Massive data volume, velocity, and variety from millions of apps and services •  MNOs held responsible for all aspects of service, whether inside or outside the network
  7. 7. CSPs Increasingly Competing on QoE Trying to understand how network performance impacts experience When service is degraded, CSPs need to quickly understand: Is the problem inside or outside the network? Which subscribers are impacted? What needs attention first?
  8. 8. Common Operator Challenges Network Operations Customer Care Marketing Increase monetization, offset voice, SMS revenue loss Reduce churn and credits, cost to serve Reduce complexity, increase visibility, increase QoE
  9. 9. background image: 960x540 pixels - send to back of slide and set to 80% transparency Operators are turning to their data to solve these challenges How do we analyze data in an efficient, cost-effective way to transform customer experience?
  10. 10. High performance, interactive SQL queries on Hadoop HDB: The Hadoop Native SQL Database ●  Highly efficient MPP (massively parallel processing) ●  Low-latency ●  Petabyte scalability ●  ACID transaction support ●  SQL-92, 99, 2003 compatibility ●  Advanced cost-based optimizer DATA LAKE SQL App BUSINESS ANALYSTS DATA SCIENTISTS
  11. 11. Advanced Analytics Performance Exceptional MPP performance, low latency, petabyte scalability, ACID reliability, fault tolerance Most Complete Language Compliance Higher degree of SQL compatibility, SQL-92, 99, 2003, OLAP, leverage existing SQL skills Best-in-class Query Optimizer Maximize performance and do advanced queries with confidence Elastic Architecture for Scalability Scale-up/down or scale-in/out, expand/ shrink clusters on the fly Tightly integrated w/ MADlib Machine Learning Advanced MPP analytics, data science at scale, directly on Hadoop data HDB / HAWQ Advantages MAD
  12. 12. ●  Discover New Rela/onships ●  Enable Data Science ●  Analyze External Sources ●  Query All Data Types! Mul/-level Fault Tolerance Granular Authoriza/on Resource Pools + YARN Mul$-tenancy + Security ANSI SQL Standard OLAP Extensions JDBC ODBC Connec/vity MPP Architecture Online Expansion Hadoop / HDFS Petabyte Scale Cost-Based OpXYZizer Dynamic Pipelining ACID + Transac/onal Ambari Management Machine Learning Data Federa/on Language Extensions Hardened, 10+ Years Tested, Produc/on Proven Opera$ons + Extensibility HDFS Na/ve File Formats ●  Manage Mul/ple Workloads ●  Petabyte Scale Analy/cs ●  Sub-second Performance ●  Leverage Exis/ng Skills & Tools ●  Easily Integrate with Other Tools Compression + Par//oning Core compliance ●  Well Integrated with Hortonworks Data PlaZorm HDB + HDP Marketecture
  13. 13. 13 Faster Insight with In-Database Analytics Pivotal HDB / Apache HAWQ (incubating) Low-latency, MPP analytic database with full ANSI SQL support running natively on Hortonworks HDP Apache MADlib (incubating) Scale out, SQL-based machine learning within HDB/HAWQ, Greenplum, and PostgreSQL databases +
  14. 14. 14 Top MADlib Use Cases •  Fraud detection •  Risk analysis •  Customer experience •  Marketing •  Predictive maintenance
  15. 15. Telco uses HDB to analyze and improve call quality 2bn call records per day •  Overwhelmed traditional data warehouse Hadoop and HDB •  5x data stored at half the cost •  Familiar SQL interface to analyze 3 months worth of dropped call data DATA LAKE
  16. 16. 16 How could a network operations team apply analytics to improve experience for its network services?
  17. 17. What Data Is Needed? Service Assurance Customer Care Marketing • Network Performance data (GTP probe data) • HTTP Click Stream Records • Flow Records • Network & Device Reference Data • Topology and location • HTTP Click Stream Records • Flow Records • Network Performance data (GTP probe data) • CRM data (account, device information) • Service Request Records • HTTP Click Stream Records • Flow Records • CRM data (account, device information)
  18. 18. Constructing KQIs from performance indicators 84% Speed Latency Effective Throughput Integrity Drops Time-Outs Cut-Offs Failures Retainability Failure % Response time Access time Accessibility Voice QoE Data capture Data science •  xDRs •  NetFlow •  Probes Data processing Accessibility Quality Retainability
  19. 19. In-Database Analytics with HDB and MADlib Application/ Content Data •  Raw Usage •  Logs •  (HTTP, Flow, Other) HDFS HBase Hive HDB/HAWQ In-DB AnalyticsNetwork Data •  Probes (GTP-C/U) •  xDRs •  Case management •  CRM •  Billing •  Device inventory •  Network topology •  Geolocation maps B/OSS Data PXF PXF MPP Query Execution ANSI SQL •  SQL-based •  Over 50 data science functions •  UDFs •  Offline modeling •  Batch queries •  Reporting/viz with SQL-based tools + Native or PXF
  20. 20. 20 How could marketing teams use analytics to better target subscribers for promotions and advertising?
  21. 21. Blended Mobile ARPU is Declining Loss of voice and SMS ARPU from competition, free apps Data revenues not offsetting voice, SMS losses MNOs seeking new monetization options Source: IHS Technology Mobile ARPU Forecast, 2016
  22. 22. Need for Behavioral Insights •  CSPs need to maximize subscriber yields to offset declining revenues •  Marketers have little information to market to anonymous prepaid subscribers •  Need to protect current revenue from competition from over-the-top (OTT) apps and services
  23. 23. Morning: New York •  Starts on Samsung Galaxy S6 •  On CNN, sees news on earthquake •  Donates via Red Cross Society •  Later: Switches to iPad – same account plan •  Checks market close on WSJ.com A Day in the Life: User Perspective Evening: Boston •  Checks Facebook page •  Streams Netflix
  24. 24. SubscriberId StartTimeStamp EndTimeStamp URL User Agent RK2FQ9PWZVW52 2015 04 28 06 37 04 512 2015 04 28 06 37 04 543 http://www.cnn.com Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1 RK2FQ9PWZVW52 2015 04 28 06 37 05 546 2015 04 28 06 37 04 623 http://www.cnn.com/world Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1 RK2FQ9PWZVW52 2015 04 28 06 37 19 529 2015 04 28 06 37 19 599 http://www.cnn.com/2015/04/28/asia/flight-delhi- nepal-earthquake/index.html Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1 RK2FQ9PWZVW52 2015 04 28 06 37 23710 2015 04 28 06 37 23 770 http://www.cnn.com/2015/04/28/asia/kathmandu.jpg Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1 RK2FQ9PWZVW52 2015 04 28 06 37 45919 2015 04 28 06 37 45988 http://adclick.g.doubleclick.net/pics/click/?= Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1 RK2FQ9PWZVW52 2015 04 28 06 37 34957 2015 04 28 06 37 34996 http://www.google-analytics.com/__utm.gif? utmwv=4.9mi Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1 RK2FQ9PWZVW52 2015 04 28 06 42 09 883 2015 04 28 06 42 10 467 http://www.cnn.com/2015/04/25/world/nepal- earthquake-how-to-help/index.html Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1 ….. (images being loaded here) ……. RK2FQ9PWZVW52 2015 04 28 06 43 03 234 2015 04 28 06 06 12 334 http://www.nrcs.org Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) ….. ….. ….. ….. … RK2FQ9PWZVW52 2015 04 28 09 45 05 732 2015 04 28 09 45 05 812 http://wsj.com Mozilla/5.0 (iPad; CPU OS 8_1 like Mac OS X) AppleWebKit/600.1.4 (KHTML, like Gecko) Version/ 8.0 Mobile/12B410 Safari ….. ….. ….. … … RK2FQ9PWZVW52 2015 04 28 17 03 14 204 2015 04 28 17 03 14 269 http://wsj.com Mozilla/5.0 (iPad; CPU OS 8_1 like Mac OS X) AppleWebKit/600.1.4 (KHTML, like Gecko) Version/ 8.0 Mobile/12B410 Safari ….. ….. ….. … … RK2FQ9PWZVW52 2015 04 28 18 19 56 459 2015 04 28 18 19 56 509 https://69.63.178.45 ….. ….. ….. … … RK2FQ9PWZVW52 2015 04 28 21 23 25 754 2015 04 28 21 23 25 876 http://23.13.201.71 netflix-ios-app A Day in the Life: Data Perspective •  Capture and collate raw subscriber data •  Sessionize and enrich clickstream data with location, device. and other data, calculate subscriber usage metrics
  25. 25. SubscriberId DeviceNAME PUBLISHER Category- Subcategory Application Name SESSION START SESSION END PAGE_VIEWS HITS BYTES LOCATION RK2FQ9PWZVW52 Samsung Galaxy S6 CNN News News-International News CNN App 2015 04 28 06 37 04 512 2015 04 28 06 42 10 467 4 45 539123 NY RK2FQ9PWZVW52 Samsung Galaxy S6 Red Cross Non Profit & Charities-Institutions Browser 2015 04 28 06 43 03 234 2015 04 28 06 53 03 874 2 7 383372 NY RK2FQ9PWZVW52 Apple iPad Wall Street Journal News-Business & Finance News Safari Browser 2015 04 28 09 45 05 732 2015 04 28 09 55 05 732 4 40 600272 NY RK2FQ9PWZVW52 Apple iPad Wall Street Journal News-Business & Finance News Safari Browser 2015 04 28 17 03 14 204 2015 04 28 17 23 14 204 5 35 801714 NY RK2FQ9PWZVW52 Apple iPad Facebook Social Media & Networking-Social Networking - 2015 04 28 18 19 56 459 2015 04 28 18 23 21 459 318 5041054 Boston RK2FQ9PWZVW52 Apple iPad Netflix Media & Entertainment-Online Video Ne&lix App 2015 04 28 21 23 25 876 2015 04 28 23 23 24 325 6 2330 295121789 Boston Compute subscriber-level metrics and aggregates …enrich with information about content (websites or apps) and categorization, devices, and locations Aggregation and Enrichment
  26. 26. Insights: Marketing to Prepaid Users •  With data science, operators can infer gender and approximate age from subscriber activity •  Classify according to segmentation schemes (e.g., who does unknown subscriber resemble from their activity) We can offer advertisers anonymized subscriber info mapped to standard marketing/advertising categories (e.g., IAB) based on activity
  27. 27. Marketing Questions We Can Answer with Analytics • How will subscribers respond to changes in pricing? • How do we market to anonymous pre-paid subscribers? • Who’s likely to respond to an offer? • Which OTT apps threaten our own branded apps? • Which groups should we target with advertising?
  28. 28. Pivotal and Hortonworks are partnering to help companies use their data for better customer outcomes
  29. 29. Learn more •  Videos: bit.ly/MADlibvideos •  Project: madlib.incubator.apache.org •  Downloads: bit.ly/getMADlib •  Videos: bit.ly/HDBvideos •  Project: hawq.incubator.apache.org •  Commercial: pivotal.io/pivotal-hdb •  Downloads: bit.ly/getHDB
  30. 30. Let’s build something MEANINGFUL

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